Detection of bacterial species present in clinical samples can direct therapeutic decision making, so tests with high sensitivity and specificity are required. Bacteria such as staphylococci that may cause disease, however, are also ubiquitously present in the environment and, if inadvertently introduced into a sample or test reagent, result in false positive detection. Numerous approaches have addressed the question of determining if a given target population present in a clinical specimen is potentially disease causing using quantitative, real-time polymerase chain reaction (qPCR). In one qPCR approach, a cycle threshold (Ct) is established whereupon any nasal swab sample that generates detectable signal from amplification of Staphylococcus aureus target nucleic acid present in the sample at a cycle number greater than Ct is deemed non-viable, a contaminant, or at a level too low to cause disease. Another method exposes samples containing cells or viruses to propidium monoazide, which can crosslink DNA in lysed cells or RNA in inactive viruses when illuminated with light, but not in intact or viable cells or viruses. The resulting cross-linked DNA or RNA cannot be amplified. Therefore, in this method, any detected amplified DNA or RNA can only be derived from intact cells or viruses.
Each of these methods, however, comes with its own drawbacks. For example, in the cycle threshold method, various components in a clinical sample may impact the efficiency of the qPCR reaction, creating imprecision in the Ct value likely resulting in lower detection sensitivity. In the case of the crosslinking method, only cells with compromised membranes or cell walls will have their DNA exposed for crosslinking treatment, thereby increasing the signal generated during cycling by non-dividing or dead but un-lysed or intact cells. Additionally, these methods are not useful in approaches that are non-quantitative and do not detect amplification in real-time. In these approaches, generally referred to as end point detection, nucleic acids are amplified, and the resulting product is detected after completion of the amplification reaction. End point detection detects whether or not a target nucleic acid has been amplified to detectable levels. Differences in sample matrix from sample to sample such as concentration of components that can inhibit amplification reactions in blood or stool can affect the speed of amplifying nucleic acids to detectable levels. Because of this, one cannot easily determine when to stop the amplification reaction such that differences in starting amounts of nucleic acid targets are reflected in the amount of target nucleic acid amplified. Additionally, end point detection methods such as planar surface DNA arrays are generally only semi-quantitative with poor dynamic range of quantitation. As a result, differences in amount of nucleic acid target present in a sample cannot be reliably used to distinguish viable and non-viable organisms using end point detection.
Therefore, there is a need for an improved method of distinguishing between viable, truly infecting pathogens and dead or contaminating pathogens, especially in end point detection approaches.